Genomic optimization of evolution and population structure in honey bee

Genomic selection can help in more accurate estimation of breeding values, genetic improvement resulting from a more precise and better selection of individuals, as well as control of inbreeding in animals. genomic simulation made it possible to make the necessary predictions before carrying out expensive genomic processes. The success of any breeding program depends significantly on how the base population is created. All the genetic diversity of the traits included in the breeding goal must be created in the base population. Therefore, it is essential to design a program to create a base population in linkage disequilibrium by simulating random mating between bee communities in breeding processes by considering bees' genetic characteristics and reproductive behavior. In this research, the genetic architecture of the honey bee was created by simulating various demographic and genomic factors using MATLAB software, and while investigating the effect of the effective population size with the NeEstimator software in four levels of minimum allelic frequency and in the generation with the maximum linkage disequilibrium, the impact of the number of queens and males in historical generations was studied and determined. Continuity disequilibrium occurs and increases, and conversely, as the mutation rate increases, the time to reach the maximum linkage disequilibrium decreases. Increasing the number of markers in populations with fewer individuals in historical generations decreased the time to reach maximum linkage disequilibrium. Linkage disequilibrium pattern in the genome is a powerful sign of the genetic processes of the population that construct it.